Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you'll learn the fundamentals of Bayesian inference and deep learning.

For each category of algorithm, you'll go from math-first principles to a hands-on implementation in Python, exploring dozens of examples from across all the fields of machine learning. Each example is accompanied by worked-out derivations and details, as well as insightful code samples and graphics.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.